Investigatory events are frequently used to determine whether an underlying protocol or substance is effective at achieving target results. For a particular investigatory event, a degree to which the target result(s) are achieved can be determined based on (for example) a population assessment of a set of individual results corresponding to a set of entities. However, the target result(s) may pertain to a specific context, such that selection techniques by which the set of entities is defined is important to ensure that the result characterization is accurate. Frequently, entity selection is performed by filtering a larger entity pool using a set of entity-attribute filters as predefined for an event. However, due to variation in receipt times, comprehensiveness and definitions of attribute identification across entities, the filtering may be time intensive, of insufficient magnitude and/or imprecise. Consequently, conclusion of a given investigatory even may be delayed and/or results may be biased.
Further, one approach for the filtering is to query a database using the attribute filters (e.g., via a compound query). A query may thus involve determining, for each entity in the entity pool and for each attribute filter, whether the entity's attribute satisfies a filter. This type of comprehensive assessment can be resource and time intensive.